public void MutationTest1()
{
int populationSize = 2000;
file = root + "\\bays29.xml";
XDocument tspFile = XDocument.Load(file);
AdjacencyMatrix testMatrix = new AdjacencyMatrix(tspFile);
PMXCrossover crossover = new PMXCrossover((float)(0.80));
TournamentSelection selector = new TournamentSelection((int)populationSize / 2);
InversionMutation inv = new InversionMutation((float)0.05);
GeneticSolver solver = new GeneticSolver(testMatrix, inv, crossover, selector, populationSize, 10);
List <Candidate> listCand = solver.randomPopulation();
Candidate parentX = listCand[0];
Candidate parentY = listCand[1];
parentX.chromoson = new List <int>()
{
1, 2, 3, 4, 5, 6, 7, 8, 9
};
parentY.chromoson = new List <int>()
{
5, 3, 6, 7, 8, 1, 2, 9, 4,
};
inv.Mutate(parentX);
}
public void ItCanRandomlyInverseGenes()
{
var chromosome = GATestHelper.GetAlphabetCharacterChromosome();
var mutation = new InversionMutation();
for (int i = 0; i < 100; i++)
{
mutation.Mutate(chromosome, GATestHelper.GetTravelingSalesmanDefaultConfiguration());
}
}
public void Should_Perform_Mutation()
{
var algorithm = new InversionMutation(1);
var a = new Element(new double[] { 8D, 3D, 2D, 9D, 1D, 0D, 7D, 6D, 5D, 4D });
algorithm.Mutate(ref a, 1, 4);
var expectedData = new double[] { 8D, 1D, 9D, 2D, 3D, 0D, 7D, 6D, 5D, 4D };
Assert.Equal(expectedData, a.Data);
}